Google released DiffusionGemma, a 26B MoE experimental open model using text diffusion instead of token-by-token autoregressive decoding. It can generate blocks of text in parallel, reaching up to 4x faster output on dedicated GPUs. The model targets local, speed-sensitive workflows, but Google says its output quality is below standard Gemma 4 and recommends Gemma 4 for quality-critical production use.
The post’s title indicates a performance claim for real-time LLM inference on standard GPUs, reporting 3,000 tokens per second per request. No article body is available, so the underlying model, GPU type, batch size, latency profile, precision, serving stack, and benchmark method are not stated. The item is best treated as an inference-performance benchmark claim rather than a verified deployment guide.
Vercel recently announced in its Changelog that its AI Gateway service has launched an important update: developers can now automatically sort and route…
Vercel announced in its official Changelog that its AI Gateway service now officially supports "Fast Mode" for the Opus 4.7 model. Vercel AI Gateway is an API…
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Vercel has officially announced that Vercel Blob, its object storage solution designed for web developers, is now available across all of Vercel's service…
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In modern web development, feature flags and A/B testing are core tools for product iteration. However, traditional solutions often require additional network…
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